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带有资源冲突的Seru在线并行调度算法

江煜舟 李冬妮 靳洪博 殷勇

江煜舟, 李冬妮, 靳洪博, 殷勇. 带有资源冲突的Seru在线并行调度算法. 自动化学报, 2022, 48(2): 444−459 doi: 10.16383/j.aas.c190698
引用本文: 江煜舟, 李冬妮, 靳洪博, 殷勇. 带有资源冲突的Seru在线并行调度算法. 自动化学报, 2022, 48(2): 444−459 doi: 10.16383/j.aas.c190698
Jiang Yu-Zhou, Li Dong-Ni, Jin Hong-Bo, Yin Yong. An online algorithm for parallel scheduling of serus with resource conflicts. Acta Automatica Sinica, 2022, 48(2): 444−459 doi: 10.16383/j.aas.c190698
Citation: Jiang Yu-Zhou, Li Dong-Ni, Jin Hong-Bo, Yin Yong. An online algorithm for parallel scheduling of serus with resource conflicts. Acta Automatica Sinica, 2022, 48(2): 444−459 doi: 10.16383/j.aas.c190698

带有资源冲突的Seru在线并行调度算法

doi: 10.16383/j.aas.c190698
基金项目: 内蒙古自治区重大基础研究开放课题(GZ2018KF001), 国家自然科学基金(61763046)资助
详细信息
    作者简介:

    江煜舟:北京理工大学计算机学院博士研究生. 主要研究方向为赛如生产智能优化. E-mail: jiang_yuzhou@163.com

    李冬妮:北京理工大学计算机学院教授. 主要研究方向为智能优化与仿真计算, 智慧工厂与数字孪生. 本文通信作者. E-mail: ldn@bit.edu.cn

    靳洪博:北京理工大学计算机学院博士研究生. 主要研究方向为赛如生产智能优化. E-mail: hb@bit.edu.cn

    殷勇:同志社大学商学院教授. 主要研究方向为赛如生产与工业4.0. E-mail: yyin@mail.doshisha.ac.jp

An Online Algorithm for Parallel Scheduling of Serus With Resource Conflicts

Funds: Supported by State Key Laboratory of Smart Manufacturing for Special Vehicles and Transmission Systems (GZ2018KF001), National Natural Science Foundation of China (61763046)
More Information
    Author Bio:

    JIANG Yu-Zhou Ph. D. candidate at the School of Computer Science, Beijing Institute of Technology. Her research interest covers seru production and intelligent optimization

    LI Dong-Ni Professor at the School of Computer Science, Beijing Institute of Technology. Her research interest covers intelligent optimization and simulation, smart factory and digital twin. Corresponding author of this paper

    JIN Hong-Bo Ph. D. candidate at the School of Computer Science, Beijing Institute of Technology. His research interest covers seru production and intelligent optimization

    YIN Yong Professor at the Graduate School of Business, Doshisha University. His research interest covers seru production and Industry 4.0

  • 摘要: 随着大规模定制的市场需求日趋显著, 赛如生产系统(Seru production system, SPS)应运而生, 逐渐成为研究和应用领域的热点. 本文针对带有资源冲突的Seru在线并行调度问题进行研究, 即需要在有限的空间位置上安排随动态需求而构建的若干Seru, 以总加权完工时间最小为目标, 决策Seru的构建顺序及时间. 先基于平均延迟最短加权处理时间(Average delayed shortest weighted processing time, AD-SWPT)算法, 针对其竞争比不为常数的局限性, 引入调节参数, 得到竞争比为常数的无资源冲突的Seru在线并行调度算法. 接下来, 引入冲突处理机制, 得到有资源冲突的Seru在线并行调度算法, αAD-I (α-average delayed shortest weighted processing time-improved)算法, 特殊实例下可通过实例归约的方法证明其竞争比与无资源冲突的情况相同. 最后, 通过实验, 验证了在波动的市场环境下算法对于特殊实例与一般实例的优越性.
  • 图  1  AD-SWPT与$\alpha$AD-SWPT算法流程图

    Fig.  1  The flow charts of AD-SWPT and $\alpha$AD-SWPT

    图  2  按照$\alpha $AD-SWPT安排方案的构建时间示意图

    Fig.  2  Processing sub-queues in terms of starting time in the $\alpha $AD-SWPT schedule

    图  3  $f(\alpha)$$g(\alpha)$的图像

    Fig.  3  Graphs of $f(\alpha)$ and $g(\alpha)$

    图  4  三个算法的竞争比

    Fig.  4  Graphs of each algorithm' competitive ratio

    图  5  $ \alpha $AD-I算法流程图

    Fig.  5  The flow chart of $ \alpha $AD-I

    图  6  $\alpha $AD-I算法在特殊实例$I^*$下的实验结果

    Fig.  6  The experimental results of $\alpha $AD-I in $I^*$

    图  7  $\alpha $AD-I算法在一般实例下的实验结果

    Fig.  7  The experimental results of $\alpha $AD-I in general instances

    图  8  $\alpha $AD-I算法在I*与一般实例下实验结果对比

    Fig.  8  The comparision between $\alpha $AD-I in I* and $\alpha $AD-I in general instances

    图  9  $\alpha $AD-I算法与AD-SWPT改进算法在一般实例下的实验结果对比

    Fig.  9  The comparision between $\alpha $AD-I and improved AD-SWPT in general instances

    表  1  基本符号说明

    Table  1  Basic symbolic explanation

    符号说明
    $t$ 当前时刻
    $\hat{p}_j(t)$ 对于一个可行的安排方案, 在时刻$t$, 任务/$Seru$ $J_j$还剩余的处理时间, 若在时刻$t$, 该任务/$Seru$还未开始运作, 那么$\hat{p}_j(t)=p_j$
    $\sigma(\cdot)$ 一般实例下, 应用相应算法所得到的安排方案, 也用于表示对应的目标值, 在本文中即为总加权完工时间$\displaystyle\sum w_j C_j$
    $S_j$ 任务/$Seru$ $J_j$在安排方案$\sigma(\cdot)$中的构建时间
    $C_j$ 任务/$Seru$ $J_j$在安排方案$\sigma(\cdot)$中的完工时间
    ${\text{π}}(\cdot)$ 一般实例下, 应用最优离线算法所得到的安排方案, 也用于表示对应的目标值, 在本文中即为总加权完工时间$\displaystyle\sum w_j C_j$
    下载: 导出CSV

    表  2  无冲突时的特殊实例符号说明

    Table  2  Symbolic explanation of four special instances without conflicts

    符号说明
    $I_1$ 由$\alpha$AD-SWPT 算法生成的安排方案满足在所有的位置中, 最早的 SPoint 和最晚的 EPoint 之间, 不存在任何时刻$t$所有位置都闲置的一类实例
    $I'_1$ 满足$I_1$的结构, 且满足在$\alpha$AD-SWPT 算法生成的安排方案下, 最后一个子队列中所有$Seru$的加权处理时间相同的一类实例
    $I_2$ 满足$I_1$的结构, 且满足所有$Seru$的加权处理时间相同的一类实例
    $I_3$ 满足$I_1$的结构, 且满足在$\alpha$AD-SWPT 算法生成的安排方案下, 最后一个子队列中所有$Seru$的权重无穷大的一类实例
    下载: 导出CSV

    表  3  有冲突时的特殊实例符号说明

    Table  3  Symbolic explanation of four special instances with conflicts

    符号 说明
    $F$ 冲突集合, 实例中所有带有资源冲突的$Seru$的集合
    $I^*$ 冲突集合$F$中, 先构建的$Seru$与后构建的$Seru$完工时间的比值总是不大于$(1+1/m)/2$的一类实例
    $I^*_2$ 满足$I^*$的结构, $\alpha$AD-I 算法生成的安排方案下, 最早的 SPoint 和最晚的 EPoint 之间, 不存在任何时刻$t$, 所有位置都闲置; 且所有$Seru$的加权处理时间相同的一类实例
    $I^*_3$ 满足$I^*$的结构, $\alpha$AD-I 算法生成的安排方案下, 最早的 SPoint 和最晚的 EPoint 之间, 不存在任何时刻$t$, 所有位置都闲置; 且最后一个子队列中所有$Seru$的权重无穷大的一类实例
    下载: 导出CSV
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出版历程
  • 收稿日期:  2019-10-09
  • 录用日期:  2020-02-07
  • 网络出版日期:  2021-09-23
  • 刊出日期:  2022-02-18

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